1. Field of the Invention
The present invention relates to providing ubiquitous access to data resources even where such data resources are maintained in separate stores and by entirely separate processes.
2. Description of Related Art
The operation of a modern large business enterprise relies heavily upon the processing, storing, communicating and manipulation of vast amounts of information. This is particularly true of a large service company, such as a global telecommunications company. The types of information vary widely and may include, for example, customer data, employee data, account information, traffic and revenue statistics, and engineering data such as network topology and provisioning data. The vital information that supports a large enterprise may even include the software instructions that drive various elements and systems in a telecommunications network. Some information is relatively static, such as the name or address of a customer, whereas other forms of information, such as the momentary operational status of a network element, can change abruptly and must be communicated as quickly as possible to points where the information is needed.
Traditionally, the various types of information that support a large enterprise have been treated separately. Each principal function in the company, such as human resources, customer service, or engineering, has been self-contained in its use and maintenance of the data needed by that function. Each function typically selects its own tools (software applications and hardware platforms), populates its own data store, and institutes its own procedures with little regard to the remainder of the enterprise. In cases where there has been limited sharing of data between functions, the implementation has often been an ad hoc gateway between divergent systems and approaches.
It is becoming widely recognized in the field of information technology that it is not only advantageous, but essential to use a comprehensive approach to managing the data in a large enterprise.
Various approaches have been applied in an attempt to achieve ubiquitous access to data. One approach is to maintain all of the data in one central location. As the amount of data grows, this approach rapidly leads to a bottleneck at the servers as many “clients” attempt to simultaneously access the body of data. Furthermore, the remote access to the data requires a communications infrastructure and may consume considerable bandwidth.
To relieve these constraints, a different approach involves replicating the data at many distributed sites. In most cases, it is usually not known beforehand what particular data may be needed at a given site, so the entire data store must be replicated at each site. While this divides the demands upon the access to the data, this approach introduces problems in maintaining synchronization among the copies of the data Furthermore, the replication multiplies the overall storage resources needed, which can be very substantial. If a design is chosen that replicates the data as needed to maintain a certain level of performance in accessing the data, then the overall storage may actually grow as the square of the data size.
As a compromise between centralization and replication, a caching approach can be used wherein local data stores are used to partially duplicate only those portions of the overall data that are needed locally. Typically, in response to requests from points of use that rely on the cache, the local cache selectively downloads data only on an as-needed basis. The cache will accumulate a self-forming subset of the overall data. Once loaded, a particular data item in the local cache may be held indefinitely or may be discarded after a time according to a caching algorithm. Schemes have also been deployed for ensuring that data in the cache is kept current as changes occur in the corresponding data in the master data store. Although a distributed approach introduces some complexities, there are some advantages to be gained.